首页|Patent Issued for Implicitly annotating textual data in conversational messaging (USPTO 11989502)
Patent Issued for Implicitly annotating textual data in conversational messaging (USPTO 11989502)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
The following quote was obtained by the news editors from the background informa tion supplied by the inventors: “Supervised classification task models are train ed using examples consisting of utterances (strings of text in a natural languag e such as English), and a label which classifies the utterance into one of sever al classes (commonly called intents in the literature). For example, the classif ication may be as simple as “Positive”, “Negative”, and “Neutral”, and one wishe s to classify individual utterances based on the sentiment therein. “Yay that’s great” may be classified as “Positive” while “Terrible, just terrible” may be cl assified as “Negative”. This is one simple example, and in general the classific ation ontology may be arbitrarily complex, with tens, hundreds, or more possible classes.
NETL
NSTL
